{"id":"W2105551687","doi":"10.1109/tvlsi.2005.850098","title":"Global passivity enforcement algorithm for macromodels of interconnect subnetworks characterized by tabulated data","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","topic":"Electrostatic Discharge in Electronics","field":"Engineering","cited_by":126,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Passivity; Interconnection; Computer science; Enforcement; Transient (computer programming); Algorithm; Control theory (sociology); Electronic engineering; Engineering; Computer network; Electrical engineering; Artificial intelligence; Control (management)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005855538,0.0004302971,0.0005924419,0.0001330738,0.0001518585,0.0001182111,0.0005125429,0.0002754107,0.0001100915],"category_scores_gemma":[0.000006089657,0.0004277197,0.000182592,0.0003937199,0.00004292197,0.0007919689,0.000004402339,0.000361408,0.00002262337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006547112,"about_ca_system_score_gemma":0.00007870545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008707164,"about_ca_topic_score_gemma":0.000620519,"domain_scores_codex":[0.9972843,0.000114434,0.0009882963,0.0005108174,0.0004075896,0.0006945922],"domain_scores_gemma":[0.9985301,0.0001357424,0.0001944958,0.0007970068,0.0002031608,0.0001394294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004852198,0.00176897,0.00001387501,0.0006311756,0.001566765,0.00000380115,0.00109477,0.4304393,0.06645644,0.0009647292,0.01459707,0.4819779],"study_design_scores_gemma":[0.001297141,0.0002104865,0.000001397844,0.0001788139,0.0001088602,0.00001597512,0.0001438489,0.942058,0.04381673,0.00003210049,0.01176664,0.0003700347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01681298,0.0005174667,0.9722923,0.0000465832,0.001427528,0.001491909,0.006886529,0.0003533204,0.0001713862],"genre_scores_gemma":[0.9944158,0.0002439252,0.002746516,0.00004666784,0.000187195,0.00053207,0.00137511,0.00007626749,0.0003764984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9776028,"threshold_uncertainty_score":0.9998175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215667967682705,"score_gpt":0.2488577853227062,"score_spread":0.2367011056458792,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}